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Add Janus-1.3B#541

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kennymckormick merged 3 commits intoopen-compass:mainfrom
hills-code:janus
Oct 23, 2024
Merged

Add Janus-1.3B#541
kennymckormick merged 3 commits intoopen-compass:mainfrom
hills-code:janus

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We add Janus-1.3B model to reproduce the results in paper.

MME MMB
(w/o circular)
SEED MMMU_DEV_VAL MM-Vet POPE
VLMEvalkit (Reproduce) 1342.4 69.8 63.8 31.2 36.8 85.5 (overall)
87.1 (random)
Paper 1338.0 69.4 63.7 30.5 34.3 87 (random)

You can run the evaluation with the following code:

torchrun --nproc-per-node=8 run.py --data POPE MMMU_DEV_VAL MMBench_DEV_EN MME SEEDBench_IMG MMVet --model janus_1.3b --verbose

Note:

  • We evaluate MMBench without circular mode. You should set circular=False in the file vlmeval/dataset/image_mcq.py
  • We use the official evaluation of MM-Vet with GPT-4 evaluator.

@kennymckormick kennymckormick merged commit f4646f7 into open-compass:main Oct 23, 2024
kennymckormick added a commit to white2018/VLMEvalKit that referenced this pull request Nov 1, 2024
* add janus eval

* update

* [Fix] Fix Lint

---------

Co-authored-by: wuchengyue <hillwu@deepseek.com>
Co-authored-by: kennymckormick <dhd.efz@gmail.com>
kushal-tri pushed a commit to kushal-tri/VLMEvalKit that referenced this pull request Nov 22, 2024
* add janus eval

* update

* [Fix] Fix Lint

---------

Co-authored-by: wuchengyue <hillwu@deepseek.com>
Co-authored-by: kennymckormick <dhd.efz@gmail.com>
@wusize
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wusize commented Feb 11, 2025

We add Janus-1.3B model to reproduce the results in paper.

MME MMB
(w/o circular) SEED MMMU_DEV_VAL MM-Vet POPE
VLMEvalkit (Reproduce) 1342.4 69.8 63.8 31.2 36.8 85.5 (overall)
87.1 (random)
Paper 1338.0 69.4 63.7 30.5 34.3 87 (random)
You can run the evaluation with the following code:

torchrun --nproc-per-node=8 run.py --data POPE MMMU_DEV_VAL MMBench_DEV_EN MME SEEDBench_IMG MMVet --model janus_1.3b --verbose

Note:

  • We evaluate MMBench without circular mode. You should set circular=False in the file vlmeval/dataset/image_mcq.py
  • We use the official evaluation of MM-Vet with GPT-4 evaluator.

Hi! There are two splits in MMMU_DEV_VAL, i.e., dev and validation. May I know which one the numbers in the table correspond to?

@charlesCXK
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We add Janus-1.3B model to reproduce the results in paper.
MME MMB
(w/o circular) SEED MMMU_DEV_VAL MM-Vet POPE
VLMEvalkit (Reproduce) 1342.4 69.8 63.8 31.2 36.8 85.5 (overall)
87.1 (random)
Paper 1338.0 69.4 63.7 30.5 34.3 87 (random)
You can run the evaluation with the following code:

torchrun --nproc-per-node=8 run.py --data POPE MMMU_DEV_VAL MMBench_DEV_EN MME SEEDBench_IMG MMVet --model janus_1.3b --verbose

Note:

  • We evaluate MMBench without circular mode. You should set circular=False in the file vlmeval/dataset/image_mcq.py
  • We use the official evaluation of MM-Vet with GPT-4 evaluator.

Hi! There are two splits in MMMU_DEV_VAL, i.e., dev and validation. May I know which one the numbers in the table correspond to?

Hi, it was VAL set~

Mercury7353 pushed a commit to Mercury7353/VLMEvalKit that referenced this pull request Apr 28, 2025
* add janus eval

* update

* [Fix] Fix Lint

---------

Co-authored-by: wuchengyue <hillwu@deepseek.com>
Co-authored-by: kennymckormick <dhd.efz@gmail.com>
Koii2k3 pushed a commit to wjnwjn59/VLMEvalKit that referenced this pull request Nov 13, 2025
* add janus eval

* update

* [Fix] Fix Lint

---------

Co-authored-by: wuchengyue <hillwu@deepseek.com>
Co-authored-by: kennymckormick <dhd.efz@gmail.com>
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4 participants